QMAK: Interacting with Machine Learning Models and Visualizing Classification Process

• Autorzy: Wojna Arkadiusz , Jachim Katarzyna , Kosson Łukasz , Kowalski Łukasz , Mański Damian , Mański Michał , Mroczek Krzysztof , Niemkiewicz Krzysztof , Piszczatowski Robert , Próchniak Maciej , Romańczuk Tomasz , Skibiński Piotr , Staszczyk Marcin , Szostakiewicz Michał , Tur Leszek , Wójcik Damian , Zuchniak Maciej

Identyfikatory

DOI

10.15439/2023F4101

• Języki publikacji: EN

Abstrakty

EN

In various classification problems beside high accuracy data analysts expect often understanding and certain insight into the process of classification. To help them understand why a trained model selects a particular decision, how confident it is in the assigned decision, and to enable interactive improvement of trained models we present QMAK. The tool visualizes not only classification models but also the processes classifying individual objects. Five classical machine learning models and their classification process are visualized with QMAK: neural network, decision tree, k nearest neighbors, classifier based on principal component analysis (PCA) and rough set based classifier. QMAK provides also exemplary functions enabling users to modify trained models interactively.

Słowa kluczowe

EN

explainable machine learning; classification visualization; interactive classifier

PL

uczenie maszynowe; wizualizacja; klasyfikator

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2023
• Tom: Vol. 35
• Strony: 315--318
• Opis fizyczny: Bibliogr. 15 poz., rys.

Twórcy

autor

Wojna Arkadiusz

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Jachim Katarzyna

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Kosson Łukasz

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Kowalski Łukasz

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Mański Damian

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Mański Michał

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Mroczek Krzysztof

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Niemkiewicz Krzysztof

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Piszczatowski Robert

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Próchniak Maciej

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Romańczuk Tomasz

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Skibiński Piotr

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Staszczyk Marcin

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Szostakiewicz Michał

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Tur Leszek

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Wójcik Damian

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

autor

Zuchniak Maciej

• University of Warsaw Faculty of Mathematics, Informatics and Mechanics Banacha 2, 02-097 Warsaw, Poland

Bibliografia

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• 9. A. Wojna, R. Latkowski, and Ł. Kowalski, RSESLIB: User Guide, accessed: 2023-05-15. [Online]. Available: http://rseslib.mimuw.edu.pl/rseslib.pdf
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• 13. K. I. Diamantaras and S. Y. Kung, Principal Component Neural Networks: Theory and Applications. New York: John Wiley & Sons, Inc., 1996.
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• 15. A. Skowron and C. Rauszer, “The discernibility matrices and functions in information systems,” in Intelligent Decision Support, Handbook of Applications and Advances of the Rough Sets Theory, R. Slowinski, Ed. Dordrecht: Kluwer Academic Publishers, 1992, pp. 331–362.

Uwagi

1. Main Track Short Papers

2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).